AIMC Topic: Humans

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Toward Deploying a Deep Learning Model for Diagnosis of Rhabdomyosarcoma.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc

Deep learning in rheumatological image interpretation.

Nature reviews. Rheumatology
Artificial intelligence techniques, specifically deep learning, have already affected daily life in a wide range of areas. Likewise, initial applications have been explored in rheumatology. Deep learning might not easily surpass the accuracy of class...

First clinical experiences of robotic gastrectomy for gastric cancer using the hinotori™ surgical robot system.

Surgical endoscopy
BACKGROUND: Although the da Vinci™ Surgical System is the most predominantly used surgical robot worldwide, other surgical robots are being developed. The Japanese surgical robot hinotori™ Surgical Robot System was launched and approved for clinical ...

What is meant by 'integrated personalized diabetes management': A view into the future and what success should look like.

Diabetes, obesity & metabolism
Integrated personalized diabetes management (IPDM) has emerged as a promising approach to improving outcomes in patients with diabetes mellitus (DM). This care approach emphasizes the integration and coordination of different providers, including phy...

Machine Learning-Enabled Environmentally Adaptable Skin-Electronic Sensor for Human Gesture Recognition.

ACS applied materials & interfaces
Stretchable sensors have been widely investigated and developed for the purpose of human motion detection, touch sensors, and healthcare monitoring, typically converting mechanical/structural deformation into electrical signals. The viscoelastic stra...

Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches.

Sensors (Basel, Switzerland)
Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we me...

Data-centric artificial olfactory system based on the eigengraph.

Nature communications
Recent studies of electronic nose system tend to waste significant amount of important data in odor identification. Until now, the sensitivity-oriented data composition has made it difficult to discover meaningful data to apply artificial intelligenc...

Prediction of emergency department revisits among child and youth mental health outpatients using deep learning techniques.

BMC medical informatics and decision making
BACKGROUND: The proportion of Canadian youth seeking mental health support from an emergency department (ED) has risen in recent years. As EDs typically address urgent mental health crises, revisiting an ED may represent unmet mental health needs. Ac...

Multimodal Biomedical Image Segmentation using Multi-Dimensional U-Convolutional Neural Network.

BMC medical imaging
Deep learning recently achieved advancement in the segmentation of medical images. In this regard, U-Net is the most predominant deep neural network, and its architecture is the most prevalent in the medical imaging society. Experiments conducted on ...